.. This work is licensed under a Creative Commons Attribution 3.0 Unported License. http://creativecommons.org/licenses/by/3.0/legalcode ========================================== Storage Capacity Balance Strategy ========================================== https://blueprints.launchpad.net/watcher/+spec/storage-capacity-balance As of now, Watcher optimizes only compute nodes. Storage optimization is also an important feature for centralized storage (non distributed storage). This spec will add Storage Capacity Balance Strategy to balance the storage capacity, which can be also considered a way to balance the storage workload. And we can use existing goal(workload_balancing) and action(volume_migrate) for this storage capacity balance. Problem description =================== In current Data Center, the capacity of storage back-end may be not balanced, some are extremely high, some are idle. This situation will degrade the performance of I/O Read/Write, which will finally affect the QoS. This problem can be solved by storage capacity balance strategy. This strategy migrates volumes based on the capacity utilization of the cinder pools. It makes decision to migrate a volume whenever a pool's capacity utilization % is higher than the specified threshold. The migration of a volume should make the capacity utilization of the pool where it locates lower than the storage capacity utilization threshold. Use Cases ---------- As an administrator, I want to be able to trigger an audit that controls the storage capacity utilization below a certain threshold. Proposed change =============== * Extend base strategy classes to add one new strategy - " Storage Capacity Balance Strategy" * Use Cinder client to get all volumes with status in available or in-use and no snapshots, and to get all pools except the pools listed as exclude_pools in the configuration file. * Group volume pools into two categories: underload or overload pools according to threshold: .. code-block:: python under_pools = list(filter(lambda p: float(p.total_capacity_gb) - float(p.free_capacity_gb) < float(p.total_capacity_gb) * threshold, pools)) over_pools = list(filter(lambda p: float(p.total_capacity_gb) - float(p.free_capacity_gb) >= float(p.total_capacity_gb) * threshold, pools)) * Determine migrate_volumes, source pools and destination pools based on some factors: * whether a volume is mounted to a VM * volume size, * whether a volume is a mirrored volume * priority Alternatives ------------ None Data model impact ----------------- None REST API impact --------------- None Security impact --------------- None Notifications impact -------------------- None Other end user impact --------------------- None Performance Impact ------------------ None Other deployer impact --------------------- None Developer impact ---------------- None Implementation ============== Assignee(s) ----------- Primary assignee: , Work Items ---------- 1. Define proper threshold 2. Write the execute function to locate pool overloaded 3. Function to generate actions:volume_migrate or volume_retype. Dependencies ============ None Testing ======= Unit and functional test are needed. Documentation Impact ==================== Add docs on how to use this strategy. References ========== None History ======= None